• Use distributed artificial intelligence techniques to streamline the supply. • Allows to set profiles of distribution according to the characteristics and temporal needs of users. • Can use external information to anticipate demand and establish preventive actions. It could use for example, information about the upcoming weather forecasts and establish the possible energy contributions from sources of generation based on renewable energies. • The behavior is dynamic and progressive, since it is capable of learning from the corrective actions that the user can set. • The system takes into account the storing of energy or batteries available, taking advantage of the surplus to minimize the events of power shortages. • Controls the behavior of devices that require power, optimizing its consumption and prioritizing those most needed according to the requirements of the users. • The system is scalable and distributed, which can be later expanded and in case of any failure, the rest of the system would still be operating.

Description of the technology

The research group of computer engineering and networks of computers of the University of Alicante has developed an innovative system that enables the distribution and management of the electricity in a more efficient and rational way. The system uses artificial intelligence techniques to predict energy demand and taking optimal decisions about sources of supply to be used and prioritizing those preferential consumption centers. These decisions are based on rational criteria, such as the characteristics of the consumption centers, the expectations of supply, demand characteristics and previous experiences. This technology allows to reduce consumption and optimize the operation of the electric system. It means greater energy efficiency and a considerable reduction in costs. It is also suitable for environments where power fluctuates or is scarce.

Specifications

The distribution and energy management system is structured in three subsystems listed below: 1. Decision-making unit. Processing algorithms and strategies to optimize energy management. 2. Power unit. It regulates the power supplied. t is composed by the inputs and outputs of the network. 3. Control Unit. Manages the behavior of consumption centres so that they conform to available energy supply. Each of these units, physically, is implemented through two different types of devices called modules and agents. The modules must be installed grouped with at least one decision-making module, while the agents are autonomous and can be deployed at any point in the installation. These devices are connected to the different elements of the system (power generators, consumption centers and storage devices) following an elaborate design established by the research group. The decision making units are capable of communicating among themselves and with the different agents in order to distribute the available power between the centres of consumption through distributed and scalable negotiation protocols. The actions to be performed by each of the modules and agents agreed between them using smart negotiation protocols. The data to make these decisions comes from the criteria of optimization, power data available in the centers of production and the energy requirements of the centres of consumption. The system is able to operate automatically, and depending on the circumstances, define sources of energy more cost-effective, optimal, use temporary storage of energy and prioritize, centers as well as enable or disable power consumption devices. Also the system can learn from the corrective measures introduced by the users, and information from external sources, such as the Internet (weather forecast, singular dates) to implement even more refined management strategies.

Main advantages of its use

Can learn and receive information from external resources to make preventive decisions and optimize its performance.

It guarantees the energy supply to consumption centres that are vital or have priority and allows to reduce energy consumption through selective shutdown of equipment and systems.

Lets customize the system and adapt to the energy needs of the users or complex patterns.

Optimizes the distribution of electrical energy in an environment using intelligent management of each of the elements of the system.

Reduces costs to prioritize domestic energy sources and reducing the demands to the public distribution network. You can also set other savings mechanisms as the demand for energy when the electric rate is reduced.

Networks of very high power, as well as those of high and medium power for transport and supply large areas, industrial areas, municipalities and urban areas.

Related keywords

Energy Management Technology

Energy Management Market

Energy Distribution

power distribution

power energy

electricity

electrical energy

energy management

energy distribution

About UNIVERSIDAD DE ALICANTE

Research & Technology Organization from Spain

UNIVERSIDAD DE ALICANTE

As one of the largest universities of Spain, Universidad de Alicante has a rich history of innovation. Our main objective is goal is to to transfer the technology that our research teams are developing to the industries and companies which are able to take profit from them. R & D & Innovation results and know-how are offered in the domains of Chemistry, Materials, Environment, IT, Building and other applied subjects.

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